63 citations · 94 across the 12 of their papers we have counts for
13 papers
Beyond Classification: Task-Dependent Learnability under Privacy-Motivated Image Transformations
Leon Ranke, Wolfgang Hübner, Ronny Hug +2
Privacy-Enhancing Technologies (PETs) in computer vision often rely on noise or image perturbations to protect visual data while securely processing it, creating a trade-off betwee…
Generating Synthetic Ground Truth Distributions for Multi-step Trajectory Prediction using Probabilistic Composite Bézier Curves
Ronny Hug, Stefan Becker, Wolfgang Hübner +1
An appropriate data basis grants one of the most important aspects for training and evaluating probabilistic trajectory prediction models based on neural networks. In this regard,…
Utilizing dataset affinity prediction in object detection to assess training data
Stefan Becker, Jens Bayer, Ronny Hug +2
Data pooling offers various advantages, such as increasing the sample size, improving generalization, reducing sampling bias, and addressing data sparsity and quality, but it is no…
Bézier Curve Gaussian Processes
Ronny Hug, Stefan Becker, Wolfgang Hübner +2
Probabilistic models for sequential data are the basis for a variety of applications concerned with processing timely ordered information. The predominant approach in this domain i…
Generating Synthetic Training Data for Deep Learning-Based UAV Trajectory Prediction
Stefan Becker, Ronny Hug, Wolfgang Hübner +2
Deep learning-based models, such as recurrent neural networks (RNNs), have been applied to various sequence learning tasks with great success. Following this, these models are incr…
MissFormer: (In-)attention-based handling of missing observations for trajectory filtering and prediction
Stefan Becker, Ronny Hug, Wolfgang Hübner +2
In applications such as object tracking, time-series data inevitably carry missing observations. Following the success of deep learning-based models for various sequence learning t…